Use of ENSO information in improving seasonal water supply outlooks.

In the Interior West, there exists a practical need for developing reservoir operating plans in January for the following seasons. Our study poses the question: Can the decisions, upon which these plans are based, be aided by climate information and predictions? We begin by reviewing the extent to which climate information currently enters the decision process. Currently, reservoir operating plans for the spring and summer in the interior western United States are based on 1 January observed snowpack and historical information, which are incorporated into operational hydrologic forecasts produced by the NOAA River Forecast Centers, the Natural Resources Conservation Service, and some reservoir operators themselves. These outlooks do not include information on how the snowpack evolution after 1 January may be influenced by potentially predictable climate phenomena, such as the El Nino/Southern Oscillation (ENSO). It has become evident from several climate studies that ENSO has an appreciable impact on western US snowpack. It is not established, however, the extent to which these general ENSO-snowpack associations are already present on January 1. Guided by the practical need for developing operating plans in January for the following several months, our study thus focuses of whether forecasts of water supply in spring and summer based on snowpack information alone can be improved upon by including information on seasonal variations in ENSO-snowpack associations. We especially focus on the ENSO signal in the period after 1 January, and how the subsequent evolution of snowpack is influenced by tropical sea surface temperatures.

To address these issues, we examine the historical effects of El Nino and La Nina events on the seasonal evolution of snow water equivalent (SWE) in the Columbia and Colorado River systems. Our analysis of the observations indicates a strong seasonal and spatial variation of ENSO impacts in the Interior West. Our predictions of spring/summer runoff based on the water stored in the mid-winter snowpack are, in almost all cases, of greater accuracy than predictions based on ENSO information alone. However, combining information on historic seasonal changes in ENSO-snowpack signals with knowledge of the water equivalent of the 1 January snow pack provides improved predictions of spring/summer runoff for basins in which ENSO-snowpack associations exhibit strong seasonality. A dynamical assessment is given that indicates our historical analysis of ENSO-snowpack associations are not simply statistical artifacts, and that they may be useful for improving operational water supply outlooks.